Shadoks Approach to Low-Makespan Coordinated Motion Planning

Author:

Crombez Loïc1ORCID,da Fonseca Guilherme D.2ORCID,Gerard Yan1ORCID,Gonzalez-Lorenzo Aldo2ORCID,Lafourcade Pascal1ORCID,Libralesso Luc1ORCID

Affiliation:

1. LIMOS, Université Clermont Auvergne, Clermont-Fd, France

2. LIS, Aix-Marseille Université, Arles, France

Abstract

This article describes the heuristics used by the Shadoks 1 team for the CG:SHOP 2021 challenge. This year’s problem is to coordinate the motion of multiple robots in order to reach their targets without collisions and minimizing the makespan. It is a classical multi-agent path finding problem with the specificity that the instances are highly dense in an unbounded grid. Using the heuristics outlined in this article, our team won first place with the best solution to 202 out of 203 instances and optimal solutions to at least 105 of them. The main ingredients include several different strategies to compute initial solutions coupled with a heuristic called Conflict Optimizer to reduce the makespan of existing solutions.

Funder

French government research program “Investissements d’Avenir”

French ANR PRC

ACTIVmap

French government IDEX-ISITE initiative

Publisher

Association for Computing Machinery (ACM)

Subject

Theoretical Computer Science

Reference33 articles.

1. Multi-agent path finding on real robots

2. Eli Boyarski, Ariel Felner, Roni Stern, Guni Sharon, Oded Betzalel, David Tolpin, and Solomon Eyal Shimony. 2015. ICBS: The improved conflict-based search algorithm for multi-agent pathfinding. In 8th Annual Symposium on Combinatorial Search (SOCS’15). 223–225. http://www.aaai.org/ocs/index.php/SOCS/SOCS15/paper/view/10974.

3. Parts-to-picker based order processing in a rack-moving mobile robots environment

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